好的，我有一张看起来像这样的表：
request我还没有列出更多列，因为它们不相关。
我要确定的是，在给定月份中Acct_id Eff_dt Expr_dt Prod_cd Open_dt
-------------------------------------------------------
111 2012-05-01 2013-06-01 A 2012-05-01
111 2013-06-02 2014-03-08 A 2012-05-01
111 2014-03-09 9999-12-31 B 2012-05-01
222 2015-07-15 2015-11-11 A 2015-07-15
222 2015-11-12 2016-08-08 B 2015-07-15
222 2016-08-09 9999-12-31 A 2015-07-15
333 2016-01-01 2016-04-15 B 2016-01-01
333 2016-04-16 2016-08-08 B 2016-01-01
333 2016-08-09 9999-12-31 A 2016-01-01
444 2017-02-03 2017-05-15 A 2017-02-03
444 2017-05-16 2017-12-02 A 2017-02-03
444 2017-12-03 9999-12-31 B 2017-02-03
555 2017-12-12 9999-12-31 B 2017-12-12
有多少帐户发生了变化，但只有一个方向发生了变化（因此本例中来自A＆gt; B）。然而，有时帐户首先作为B打开，然后更改为A.或者它打开为A，更改为B，然后移回A.我只想知道当前帐户在给定月份中的位置Prod_cd已从A更改为B.
Prod_cd是对帐户进行更改的日期（可能是任何更改，例如地址更改，名称更改或我正在寻找的内容，产品代码更改）。
Eff_dt是该行的到期日期，基本上是新更改之前的最后一天。当该行的日期是9999-12-31时，那是最新的行。
Expr_dt是帐户创建的日期。
我最初创建的查询是这样的：
Open_dt但它给了我看起来不正确的结果。我想专门跟踪发生的转换次数，但我收到的帐户数量似乎太高了。
可能有一种方法可以使用窗口函数创建更可靠的查询，但考虑到select
count(distinct acct_id)
from table
where prod_cd = 'B'
and expr_dt = '9999-12-31'
and eff_dt between '2017-12-01' and '2017-12-31'
and open_dt < '2017-12-01'
更改可能发生在多个方向，我不知道如何编写该查询。任何帮助将不胜感激！
答案 0 :(得分：1)
如果您专门寻找开关A - >; B，那么最简单的方法是使用df[1]。但是，Teradata需要略有不同的表述：
lag()我猜测日期条件是在外部查询中 - 意味着他们select count(distinct acct_id)
from (select t.*,
max(prod_cd) over (partition by acct_id order by effdt rows between 1 preceding and 1 preceding) as prev_prod_cd
from t
) t
where prod_cd = 'B' and prev_prod_cd = 'A' and
expr_dt = '9999-12-31' and
eff_dt between '2017-12-01' and '2017-12-31' and
open_dt < '2017-12-01';
不使用它们。
答案 1 :(得分：1)
与Gordon的答案类似，但是使用支持的窗口函数（而不是LAG）并使用Teradata的QUALIFY子句来执行lag-gy查找：
alabaster: 0.7.10-py36hcd07829_0 --> 0.7.10-py36_1 conda-forge
anaconda: 5.0.1-py36h8316230_2 --> custom-py36h363777c_0
anaconda-navigator: 1.6.9-py36hc720852_0 --> 1.6.12-py36hdad2993_0
anaconda-project: 0.8.0-py36h8b3bf89_0 --> 0.8.2-py36_0 conda-forge
astropy: 2.0.2-py36h06391c4_4 --> 2.0.4-py36_0 conda-forge
babel: 2.5.0-py36h35444c1_0 --> 2.5.1-py36_0 conda-forge
backports.shutil_get_terminal_size: 1.0.0-py36h79ab834_2 --> 1.0.0-py_3 conda-forge
bleach: 2.0.0-py36h0a7e3d6_0 --> 2.0.0-py_1 conda-forge
bokeh: 0.12.10-py36h0be3b39_0 --> 0.12.13-py36_0 conda-forge
bottleneck: 1.2.1-py36hd119dfa_0 --> 1.2.1-py36_1 conda-forge
ca-certificates: 2017.08.26-h94faf87_0 --> 2017.11.5-0 conda-forge
certifi: 2017.7.27.1-py36h043bc9e_0 --> 2017.11.5-py36_0 conda-forge
cffi: 1.10.0-py36hae3d1b5_1 --> 1.11.2-py36_0 conda-forge
click: 6.7-py36hec8c647_0 --> 6.7-py_1 conda-forge
cloudpickle: 0.4.0-py36h639d8dc_0 --> 0.5.2-py_0 conda-forge
comtypes: 1.1.2-py36heb9b3d1_0 --> 1.1.3-py36_0 conda-forge
cryptography: 2.0.3-py36h123decb_1 --> 2.1.4-py36_0 conda-forge
cython: 0.26.1-py36h18049ac_0 --> 0.27.3-py36_0 conda-forge
dask: 0.15.3-py36h396fcb9_0 --> 0.16.1-py_0 conda-forge
dask-core: 0.15.3-py36hd651449_0 --> 0.16.1-py_0 conda-forge
distributed: 1.19.1-py36h8504682_0 --> 1.20.2-py36_0 conda-forge
freetype: 2.8-vc14h17c9bdf_0 --> 2.8.1-vc14_0 conda-forge [vc14]
h5py: 2.7.0-py36hfbe0a52_1 --> 2.7.1-py36_2 conda-forge
hdf5: 1.10.1-vc14hb361328_0 --> 1.10.1-vc14_1 conda-forge [vc14]
html5lib: 0.999999999-py36ha09b1f3_0 --> 1.0.1-py_0 conda-forge
intel-openmp: 2018.0.0-hcd89f80_7 --> 2018.0.0-hd92c6cd_8
ipykernel: 4.6.1-py36hbb77b34_0 --> 4.8.1-py36_0 conda-forge
ipython: 6.1.0-py36h236ecc8_1 --> 6.2.1-py36_1 conda-forge
ipywidgets: 7.0.0-py36h2e74ada_0 --> 7.1.1-py36_0 conda-forge
itsdangerous: 0.24-py36hb6c5a24_1 --> 0.24-py_2 conda-forge
jedi: 0.10.2-py36hed927a0_0 --> 0.11.1-py36_0 conda-forge
jinja2: 2.9.6-py36h10aa3a0_1 --> 2.10-py36_0 conda-forge
jpeg: 9b-vc14h4d7706e_1 --> 9b-vc14_2 conda-forge [vc14]
jsonschema: 2.6.0-py36h7636477_0 --> 2.6.0-py36_1 conda-forge
jupyter_client: 5.1.0-py36h9902a9a_0 --> 5.2.2-py36_0 conda-forge
jupyter_core: 4.3.0-py36h511e818_0 --> 4.4.0-py_0 conda-forge
jupyterlab: 0.27.0-py36h34cc53b_2 --> 0.31.5-py36_1 conda-forge
jupyterlab_launcher: 0.4.0-py36h22c3ccf_0 --> 0.10.3-py36_0 conda-forge
libpng: 1.6.32-vc14h5163883_3 --> 1.6.34-vc14_0 conda-forge [vc14]
libtiff: 4.0.8-vc14h04e2a1e_10 --> 4.0.9-vc14_0 conda-forge [vc14]
libxml2: 2.9.4-vc14h8fd0f11_5 --> 2.9.5-vc14_1 conda-forge [vc14]
libxslt: 1.1.29-vc14hf85b8d4_5 --> 1.1.32-vc14_0 conda-forge [vc14]
llvmlite: 0.20.0-py36_0 --> 0.21.0-py36_0 conda-forge
lxml: 4.1.0-py36h0dcd83c_0 --> 4.1.1-py36_0 conda-forge
matplotlib: 2.1.0-py36h11b4b9c_0 --> 2.1.2-py36_0 conda-forge
mistune: 0.7.4-py36h4874169_0 --> 0.8.3-py_0 conda-forge
mkl: 2018.0.0-h36b65af_4 --> 2018.0.1-h2108138_4
mpmath: 0.19-py36he326802_2 --> 1.0.0-py_0 conda-forge
msgpack-python: 0.4.8-py36h58b1e9d_0 --> 0.5.1-py36_0 conda-forge
nbconvert: 5.3.1-py36h8dc0fde_0 --> 5.3.1-py_1 conda-forge
networkx: 2.0-py36hff991e3_0 --> 2.0-py36_1 conda-forge
nltk: 3.2.4-py36hd0e0a39_0 --> 3.2.5-py_0 conda-forge
notebook: 5.0.0-py36hd9fbf6f_2 --> 5.4.0-py36_0 conda-forge
numba: 0.35.0-np113py36_10 --> 0.36.2-np114py36h12cb543_0
numexpr: 2.6.2-py36h7ca04dc_1 --> 2.6.4-py36_0 conda-forge
numpy: 1.13.3-py36ha320f96_0 --> 1.14.0-py36h4a99626_1
openpyxl: 2.4.8-py36hf3b77f6_1 --> 2.5.0-py36_0 conda-forge
openssl: 1.0.2l-vc14hcac20b0_2 --> 1.0.2n-vc14_0 conda-forge [vc14]
pandas: 0.20.3-py36hce827b7_2 --> 0.22.0-py36_0 conda-forge
pandoc: 1.19.2.1-hb2460c7_1 --> 2.1.1-0 conda-forge
patsy: 0.4.1-py36h42cefec_0 --> 0.5.0-py36_0 conda-forge
pep8: 1.7.0-py36h0f3d67a_0 --> 1.7.1-py_0 conda-forge
pillow: 4.2.1-py36hdb25ab2_0 --> 5.0.0-py36_0 conda-forge
py: 1.4.34-py36ha4aca3a_1 --> 1.5.2-py_0 conda-forge
pycosat: 0.6.2-py36hf17546d_1 --> 0.6.3-py36_0 conda-forge
pycurl: 7.43.0-py36h086bf4c_3 --> 7.43.0.1-py36h74b6da3_0
pylint: 1.7.4-py36ha4e6ded_0 --> 1.8.1-py36_0 conda-forge
pysocks: 1.6.7-py36h698d350_1 --> 1.6.8-py36_1 conda-forge
pytables: 3.4.2-py36h71138e3_2 --> 3.4.2-py36_7 conda-forge
pytest: 3.2.1-py36h753b05e_1 --> 3.4.0-py36_0 conda-forge
python: 3.6.3-h9e2ca53_1 --> 3.6.4-0 conda-forge
pytz: 2017.2-py36h05d413f_1 --> 2017.3-py_2 conda-forge
pywavelets: 0.5.2-py36hc649158_0 --> 0.5.2-py36_1 conda-forge
pyzmq: 16.0.2-py36h38c27d9_2 --> 16.0.2-py36_3 conda-forge
rope: 0.10.5-py36hcaf5641_0 --> 0.10.7-py36_0 conda-forge
scikit-image: 0.13.0-py36h6dffa3f_1 --> 0.13.1-py36_0 conda-forge
scipy: 0.19.1-py36h7565378_3 --> 1.0.0-py36h1260518_0
seaborn: 0.8.0-py36h62cb67c_0 --> 0.8.1-py36_0 conda-forge
setuptools: 36.5.0-py36h65f9e6e_0 --> 38.4.0-py36_0 conda-forge
sphinx: 1.6.3-py36h9bb690b_0 --> 1.6.7-py36_0 conda-forge
spyder: 3.2.4-py36h8845eaa_0 --> 3.2.6-py36_0 conda-forge
sqlalchemy: 1.1.13-py36h5948d12_0 --> 1.2.1-py36_0 conda-forge
sqlite: 3.20.1-vc14h7ce8c62_1 --> 3.20.1-vc14_2 conda-forge [vc14]
toolz: 0.8.2-py36he152a52_0 --> 0.8.2-py_2 conda-forge
tornado: 4.5.2-py36h57f6048_0 --> 4.5.3-py36_0 conda-forge
vs2015_runtime: 14.0.25123-hd4c4e62_2 --> 14.0.25420-0 conda-forge
werkzeug: 0.12.2-py36h866a736_0 --> 0.14.1-py_0 conda-forge
wheel: 0.29.0-py36h6ce6cde_1 --> 0.30.0-py36_2 conda-forge
widgetsnbextension: 3.0.2-py36h364476f_1 --> 3.1.3-py36_0 conda-forge
xlrd: 1.1.0-py36h1cb58dc_1 --> 1.1.0-py_2 conda-forge
xlwings: 0.11.4-py36hd3cf94d_0 --> 0.11.7-py36_0 conda-forge